Literature DB >> 35804148

Sample size calculations for continuous outcomes in clinical nutrition.

Christian Ritz1, Mette Frahm Olsen2, Benedikte Grenov2, Henrik Friis2.   

Abstract

In nutrition research, sample size calculations for continuous outcomes are important for the planning phase of many randomized trials and could also be relevant for some observational studies such as cohort and cross-sectional studies. However, only little literature dedicated to this topic exists within nutritional science. This article reviews the most common methods for sample size calculations in nutrition research. Approximate formulas are used for explaining concepts and requirements and for working through examples from the literature. Sample size calculations for the various study designs, which are covered, may all be seen as extensions of the sample size calculation for the basic two-group comparison through the application of suitable scaling factors and, possibly, modification of the significance level. The latter is needed for sample size calculations for multi-group designs and designs involving multiple primary outcomes. Like cluster-randomized designs, these types of study designs may be more challenging than standard sample size calculations. In such non-standard scenarios, there may be a need for consulting a biostatistician. Finally, it should be stressed that there may be many ways to plan a study. The final sample size calculation provided for a grant applicant, study protocol, or publication will often not only depend on considerations and input information as described in this article but will also involve restrictions in terms of logistics and/or resources.
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.

Entities:  

Year:  2022        PMID: 35804148     DOI: 10.1038/s41430-022-01169-4

Source DB:  PubMed          Journal:  Eur J Clin Nutr        ISSN: 0954-3007            Impact factor:   4.016


  30 in total

Review 1.  Sample sizes for clinical trials with normal data.

Authors:  Steven A Julious
Journal:  Stat Med       Date:  2004-06-30       Impact factor: 2.373

2.  Best (but oft-forgotten) practices: sample size and power calculation for a dietary intervention trial with episodically consumed foods.

Authors:  Wei Zhang; Aiyi Liu; Zhiwei Zhang; Tonja Nansel; Susan Halabi
Journal:  Am J Clin Nutr       Date:  2020-07-09       Impact factor: 7.045

3.  Basic statistical concepts in nutrition research.

Authors:  Giovanna Saracino; Linda W Jennings; Jeanette M Hasse
Journal:  Nutr Clin Pract       Date:  2013-02-28       Impact factor: 3.080

4.  Tightening the clinical trial.

Authors:  J W Tukey
Journal:  Control Clin Trials       Date:  1993-08

5.  Ethics and sample size.

Authors:  Peter Bacchetti; Leslie E Wolf; Mark R Segal; Charles E McCulloch
Journal:  Am J Epidemiol       Date:  2005-01-15       Impact factor: 4.897

6.  Addition of Rye Bran and Pea Fiber to Pork Meatballs Enhances Subjective Satiety in Healthy Men, but Does Not Change Glycemic or Hormonal Responses: A Randomized Crossover Meal Test Study.

Authors:  Ursula Kehlet; Josephine Kofod; Jens J Holst; Christian Ritz; Margit D Aaslyng; Anne Raben
Journal:  J Nutr       Date:  2017-08-09       Impact factor: 4.798

7.  Probiotics and Child Care Absence Due to Infections: A Randomized Controlled Trial.

Authors:  Rikke Pilmann Laursen; Anni Larnkjær; Christian Ritz; Hanne Hauger; Kim Fleischer Michaelsen; Christian Mølgaard
Journal:  Pediatrics       Date:  2017-07-03       Impact factor: 7.124

8.  Association of pre-treatment nutritional status with change in CD4 count after antiretroviral therapy at 6, 12, and 24 months in Rwandan women.

Authors:  Elizabeth Kiefer; Donald R Hoover; Qiuhu Shi; Jean-Claude Dusingize; Mardge Cohen; Eugene Mutimura; Kathryn Anastos
Journal:  PLoS One       Date:  2011-12-28       Impact factor: 3.240

9.  Effectiveness of food supplements in increasing fat-free tissue accretion in children with moderate acute malnutrition: A randomised 2 × 2 × 3 factorial trial in Burkina Faso.

Authors:  Christian Fabiansen; Charles W Yaméogo; Ann-Sophie Iuel-Brockdorf; Bernardette Cichon; Maren J H Rytter; Anura Kurpad; Jonathan C Wells; Christian Ritz; Per Ashorn; Suzanne Filteau; André Briend; Susan Shepherd; Vibeke B Christensen; Kim F Michaelsen; Henrik Friis
Journal:  PLoS Med       Date:  2017-09-11       Impact factor: 11.069

10.  The PREVIEW intervention study: Results from a 3-year randomized 2 x 2 factorial multinational trial investigating the role of protein, glycaemic index and physical activity for prevention of type 2 diabetes.

Authors:  Anne Raben; Pia Siig Vestentoft; Jennie Brand-Miller; Elli Jalo; Mathjis Drummen; Liz Simpson; J Alfredo Martinez; Teodora Handjieva-Darlenska; Gareth Stratton; Maija Huttunen-Lenz; Tony Lam; Jouko Sundvall; Roslyn Muirhead; Sally Poppitt; Christian Ritz; Kirsi H Pietiläinen; Margriet Westerterp-Plantenga; Moira A Taylor; Santiago Navas-Carretero; Svetoslav Handjiev; Melitta A McNarry; Sylvia Hansen; Laura Råman; Shannon Brodie; Marta P Silvestre; Tanja C Adam; Ian A Macdonald; Rodrigo San-Cristobal; Nadka Boyadjieva; Kelly A Mackintosh; Wolfgang Schlicht; Amy Liu; Thomas M Larsen; Mikael Fogelholm
Journal:  Diabetes Obes Metab       Date:  2020-11-03       Impact factor: 6.577

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